Self Organizing Network Architecture

Self Organizing Network Architecture. Combining selforganizational principles with machine learning models goes back to the 1980s a prominent example are selforganizing maps (SOMs) an unsupervised learning approach that builds on abstractions of biological networks and biological morphogenesis More recently our group and others have started to explore these questions in the realm of.

Create Network For clustering problems the selforganizing feature map (SOM) is the most commonly used network This network has one layer with neurons organized in a grid Selforganizing maps learn to cluster data based on similarity For more information on the SOM see Cluster with SelfOrganizing Map Neural Network.

Cluster Data with a SelfOrganizing Map MATLAB & Simulink

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